Data Engineer Lead

Data Engineer Lead
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Role overview:

Lead the engineering delivery and productionisation of the Data Intelligence Platform for FDSS and related data capabilities. The role owns the technical path from use-case prototypes and analytical experiments to secure, governed, scalable and supportable data products and platform services.
The role you will play:

- Set the data engineering and platform delivery direction across FDSS data use cases.

- Turn prototype pipelines, models and demonstrations into repeatable production services.

- Coordinate data engineering, platform, analytics, ML, security, governance and operational disciplines around a single delivery roadmap.

Primary responsibilities:

- Own the Data Intelligence Platform engineering strategy, target architecture, roadmap and productionisation standards.

- Lead design and delivery of ingestion, event streaming, transformation, lakehouse, serving and analytical data products.

- Establish engineering patterns for batch and low-latency data, APIs, feature pipelines and authorised data access.

- Define and implement data quality, lineage, metadata, catalogue, master/reference data and reconciliation controls.

- Embed CI/CD, Infrastructure as Code, automated testing, observability, FinOps and secure configuration into the platform lifecycle.

- Lead production readiness across resilience, scalability, backup, recovery, monitoring, support, data protection and service management.

- Coordinate platform dependencies, environments, suppliers and interfaces with wider FDSS and ESCS services.

- Set technical priorities, estimate delivery, manage engineering risks and mentor data engineers.

- Support governance and stakeholder decisions with transparent measures of platform quality, readiness, performance and value.

Required skills and capabilities:

- Data engineering leadership and platform architecture

- Cloud data platforms and lakehouse patterns

- Batch, streaming and event-driven data pipelines

- SQL, Python and distributed data processing

- Data modelling, data products and semantic layers

- Data quality, observability, lineage, metadata and cataloguing

- Data governance, security, privacy and access control

- MLOps and productionisation of analytical or AI services

- CI/CD, Infrastructure as Code and automated data testing

- Reliability engineering, FinOps and service transition

Required experience:

- Leadership of data engineering delivery for a production cloud data platform.

- Experience taking prototypes, notebooks or analytical use cases through production engineering and operational acceptance.

- Experience designing scalable ingestion, transformation and serving patterns.

- Experience implementing data quality, governance, security and platform observability.

- Experience coordinating product, analytics, engineering, infrastructure, security and operational stakeholders.

Desired experience:

- Databricks, Microsoft Fabric, Azure data services, AWS data services or comparable platforms.

- Data Intelligence Platform, digital supply chain, logistics or defence data use cases.

- Event streaming, feature stores, MLOps or AI/ML platform engineering.

- Migration of sensitive enterprise data and integration with operational systems.

- Experience establishing a data platform team, engineering standards and reusable accelerators.

Clearance Requirements:

- SC required to start

- SC required for the role

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Leidos UK! Join our team and discover a culture of collaboration, innovation, diversity, trust, caring management, communication transparency, work-life balance, and overall job satisfaction...

What we do for you:
At Leidos we are PASSIONATE about customer success, UNITED as a team and INSPIRED to make a difference. We offer meaningful and engaging careers, a collaborative culture, and support for your career goals, all while nurturing a healthy